docstr: Set constant gradient clipping during the training process.
  In order to take effect, it needs to be called before fit.
  
  :param min: The minimum value to clip by.
  :param max: The maximum value to clip by.
  :return:
docstr_tok: ["Set","constant","gradient","clipping","during","the","training","process",".","In","order","to","take","effect",",","it","needs","to","be","called","before","fit",".",":","param","min",":","The","minimum","value","to","clip","by",".",":","param","max",":","The","maximum","value","to","clip","by",".",":","return",":"]
code: def set_constant_gradient_clipping(self, min, max):
      """
      Set constant gradient clipping during the training process.
      In order to take effect, it needs to be called before fit.
  
      :param min: The minimum value to clip by.
      :param max: The maximum value to clip by.
      :return:
      """
      raise NotImplementedError
  
file_path: analytics-zoo/pyzoo/zoo/orca/learn/spark_estimator.py
imports: from abc import abstractmethod
  from zoo.orca.learn.base_estimator import BaseEstimator
label_desc: Use image node_id 9 for calling the Estimator obj's underlying member method code with example usage: obj.set_constant_gradient_clipping(min, max) without return types